M5Rules generates a decision list for regression problems using separate-and-conquer. In each iteration it builds an model tree using M5 and makes the “best” leaf into a rule.

OneR builds a simple 1-R classifier, see Holte (1993).

PART generates PART decision lists using the approach of Frank and Witten (1998).

The model formulae should only use the ‘+’ and ‘-’ operators to indicate the variables to be included or not used, respectively. Argument options allows further customization. Currently, options model and instances (or partial matches for these) are used: if set to TRUE, the model frame or the corresponding Weka instances, respectively, are included in the fitted model object, possibly speeding up subsequent computations on the object.